(Cannabis Sativa L.) and Locally Adapted Native Plants

Montana Tech Library Digital Commons @ Montana Tech

Graduate Theses & Non-Theses Student Scholarship

Fall 2020

Phytoremediation of mining contaminated soil and groundwater by hemp (Cannabis sativa L.) and locally adapted native plants

Nathan Carpenter

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Part of the Geological Engineering Commons Phytoremediation of mining contaminated soil and groundwater by hemp (Cannabis sativa L.) and locally adapted native plants

by Nathan Carpenter

A non-thesis research paper submitted as part of the requirements for the degree of

Master of Science Geoscience Geochemistry Option Certificate in Ecological Restoration

Montana Tech 2020

ABSTRACT Phytoremediation is an environmentally friendly and cost-effective method of using plants to remediate soils and groundwater by extracting and accumulating contaminants in their tissues. Using locally adapted native plants is preferable to non-native species due to native species being accustomed to the environmental conditions allowing for increased plant growth and fitness. It is typical to use hyperaccumulator plant species since they will grow in soils with very high concentrations of metals and metalloids and show efficient ability to recover (phytoextraction potential) and accumulate (bioconcentration factor) the contaminants in its tissues.

This study focuses on using thirteen locally adapted native plant species and two non- native species to remediate soil and a shallow alluvial aquifer contaminated by historic mining practices in Butte, MT. A controlled greenhouse experiment using soil and groundwater from the North Side Tailings in the Butte Priority Soils Operable Unit was performed to test what plant species can tolerate the metal(loid)s present. Each species phytoextraction potential (PE%) and bioconcentration factor (BCF) was compared to a known hyperaccumulator Cannabis sativa, which shows the best metal(loid) tolerance,

PE%, and BCF. One native species, Artemisia ludoviciana, showed similar tolerance and ability to accumulate and recover Cu, Mn, and Zn to Cannabis sativa, but its total recovery was 1-19 times worse. Whereas comparing the other test species showed a significantly different and worse ability tolerate, accumulate, and recover the contaminants. Future research should be done to investigate the plants ability to accumulate and recover contaminants in its root system and compare the greenhouse experiment to a field study.

Since hemp fiber is widely used in industrial manufacturing, further research to understand how hemp fiber quality is impacted when used concurrently for remediation and industrial purposes is important.

Keywords: phytoextraction potential, bioconcentration factor, trace metals, greenhouse experiment, hyperaccumulator, Butte, Montana

INTRODUCTION

Historic mining practices in Butte, MT have left behind mine waste highly concentrated in arsenic (As), cadmium (Cd), copper (Cu), manganese (Mn), and zinc (Zn) (Tucci &

Icopini, 2012). The Parrot Tailings, North Side Tailings, and Diggings East Tailings are the most notable; they have been left untouched since mining ceased and are a significant source of soil and groundwater contamination in the area (Tucci & Icopini, 2012). This project will focus on the Northside Tailings and Diggings East Tailings located around

Upper Silver Bow Creek (USBC) in the Butte Priority Soils Operable Unit technical impractibility zone (BPSOU). Groundwater wells in this area have static water levels ranging between 1 and 3.5 meters below surface with high contaminant concentrations.

Recreational parks are planned to remediate and restore the landscape in USBC. All groundwater saturated soil will be left in place, and groundwater monitoring and management is planned to keep surface water and Silver Bow Creek contaminant-free

(EPA, 2006).

Phytoremediation is an environmentally friendly and cost-effective method of remediating contaminated soils and groundwater that typically implements the use of mycorrhizae.

Mycorrhizal fungi form a symbiotic, mutualistic relationship with plants that help establish an ecosystem, improve plant diversity, and increase plant productivity (Quoreshi, 2008).

Locally adapted native plant species and mycorrhizae are accustomed to the environmental conditions, and local mycorrhizae will improve plant growth and fitness (Crooks, 2002;

Brooks et al., 2004; Charles & Dukes, 2008; Funk et al., 2008; Rúa et al., 2016). Native plants have shown an equal or superior growth and fitness when grown in a system with non-natives (Daehler, 2003).

Traditionally industrial hemp (Cannabis sativa) had multiple uses, most importantly it has been a source of fiber and hemp seed oil. Today it is becoming popular among farmers in several states of the US, including Montana, as a multi-purpose agricultural crop and an ideal alternative for organic farming. However, the plant’s alternative uses stretch far beyond agriculture. Hemp is a hyperaccumulator meaning that it can grow in soil with very high concentrations of metals and metalloids and concentrates the contaminants in its tissues (Pal & Carpenter, 2020).

In this study, I investigated via a greenhouse experiment which native plant species can withstand the contaminant concentrations found in the soil and groundwater from the

Diggings North area, and their respective metal recovery and accumulation potential, to understand which species could be efficient in remediation purposes. In addition, Cannabis sativa was used as a non-native test species. Further, the author compared the accuracy of pXRF vs. acid digestion followed by ICP-OES as a method to quantify contaminant concentrations in the plants.

METHODS

Soil and Groundwater Collection Contaminated soil and groundwater for this project were collected in the spring of 2019 in the Butte Priority Soils Operable Unit along Upper Silver Bow Creek (Figure 1). The soil was homogenized, and analyzed for As, Cu, Fe, Mn, Pb, and Zn by acid digestions and analysis via inductively coupled optical emission spectrometry (ICP-OES) at the Montana

Bureau of Mines and Geology Analytical Laboratory.

Groundwater was collected from well GS-32S with three 55-gallon drums with a Double

Stage Geosquirt 12V DC Purge Pump. Water was stored at room temperature and purged

5 with nitrogen gas for 1.5 hours a week. Groundwater chemistry and plant growth were monitored weekly.

Figure 1. Location of soil and groundwater collection in the Butte Priority Soils Operable Unit. Soil was collected adjacent to the GS-32S groundwater well in Butte, MT.

Greenhouse Experiment The greenhouse portion of this experiment was completed in two stages. The first stage included growing hemp (Cannabis sativa) and fourteen native plant species in contaminated soil. The native species were the following: balsam poplar (Populus balsamifera), quaking aspen (Populus tremuloides), sandbar willow (Salix exigua), bluebunch wheatgrass (Pseudoroegnaria spicata), shrubby cinquefoil (Dasiphora fruticosa), white sagebrush (Artemisia ludoviciana), basin wildrye (Leymus cinereus),

6 rubber rabbitbrush (Ericameria nausesa), big sagebrush (Artemisia tridentata), giant goldenrod (Solidago gigantea), common sunflower (Helianthus annuus), tufted hairgrass

(Deschampsia caespitosa), Holbøll's rockcress (Arabis holbolea), and silky lupine (Lupinus sericeus). Seeds were germinated in a sterile petri dish with filter paper. Deepots D40L 656 mL growing pots were filled with soil collected from the study area, three cotton balls placed in the bottom, and half of the pots getting ½ inch inoculated layer of local mycorrhizae once the pot was ¾ full; mycorrhizae inoculum was collected from the West

Side soils in Butte, MT (46°00'43.49" N, 112°34'14.40" W). Preparation of the pots consisted of washing with soap, a bleach soak, and then sterilization with 70% ethanol under a UV light.

Photo 1. Phytoremediation experiment. Photo credit: Robert Pal

The second stage included the same species as stage one, except for the balsam poplar and sandbar willow live cuttings, and shrubby cinquefoil were replaced with non-native wheat

(Triticum aestivum), blanketflower (Gaillardia aristata), and hairy goldenaster

(Heterotheca villosa). In this setting seeds were directly placed in the growing pots. Five

7 seeds were germinated in the pots and thinned down to one individual as germination occurred. Ray Leach Cone-tainers SC10 164 mL were used and filled with a soil mixture of

50% contaminated and 50% potting soil with a ¼ inch inoculated layer of local mycorrhizae once the pot was ¾ full. All plants were monitored weekly with growth measurements. One gram of Osmocote 19-6-12 fertilizer and inorganic phosphate were added to each pot. Inorganic phosphate will induce plants to accept the mycorrhizae since plants cannot uptake inorganic phosphate on their own. Initial watering for all plants was done by an overhead sprinkler system for five, three-minute cycles daily until plants were large enough for the implementation of groundwater (Photo 1).

Figure 2. Treatment groups for the greenhouse experiment. No mycorrhizae indicate there will not be inoculation of mycorrhizae.

Each treatment group received weekly watering with either tap or contaminated groundwater, and either inoculation or no inoculation with mycorrhizae (Figure 2). Once watering with groundwater was implemented, all plants were in bins filled with either tap or groundwater, and they soaked for 1 hour once a week (Photo 2). Greenhouse temperature was kept at roughly 21°C during the day and at 18°C during the nighttime.

Plants were harvested after 16 weeks of growing. Plant samples were washed in tap water, roots and aboveground biomass length was measured. Afterwards plant samples were dried at 60°C for 48 hours and their above and belowground biomass was weighed separately.

Photo 2. Groundwater implementation to the greenhouse experiment.

Acid Digestion For metals and metalloid analysis soil and plant matter samples were weighed out to a dry weight of 0.5 g and divided into roots and shoot/leaf matter. Samples were digested in 15 mL trace metal cleaned digestion vessels with 3 mL of Fisher chemical trace metal nitric acid at 120°C for 4 hours. Once vessels cooled, 1 mL of 30% J.T. Baker™ hydrogen peroxide was added at 70°C for 30 minutes. 15 mL of Q-water was added to each vessel and filtered through Whatman No. 40 0.2 μm paper into a trace metal clean secondary container. Digested samples were diluted to 30 mL with 1% nitric acid. ICP-OES data were corrected for dilutions to represent the mg of metal per kg of plant digested (e.g. converting

Zn mg L-1 to mg kg-1) (Eq. 1):

1000 ∗ 푃푙푎푛푡 푍푛 푂퐸푆 푐표푛푐푒푛푡푟푎푡푖표푛 (푚푔 퐿−1 ) 푚푔 푍푛 푘푔 표푓 푝푙푎푛푡 −1 = (Eq. 1) 푚푎푠푠 표푓 푝푙푎푛푡 푑푖푔푒푠푡푒푑 (푔) ∗ 푓푖푛푎푙 푑푖푔푒푠푡푖표푛 푣표푙푢푚푒 (퐿)

Groundwater Chemistry Water samples collected for dissolved chemistry analysis were stored in 30 mL trace metal

(TM) cleaned high density polyethylene (HDPE) Nalgene bottles. Samples were filtered

across 25mm, 1.2 and 0.8/0.2 μm polyethersulfone syringe filters using a 1 L HDPE

Nalgene bottle, 140 mL polypropylene syringe, polycarbonate stop cock, and Tygon tubing

all trace-metal cleaned. 30 mL bottles used for ICP-MS were pre-acidified with 300 μL

trace metal grade concentrated nitric acid (HNO3), and ICP-OES samples were preacidifed

with 100 μL extra pure, ACROS Organics™ methanesulfonic acid (MSA) Michalski et al.,

2011; Oliveira et al., 2010). pH for each sample was measured with a WTW pH 3110 meter

with an error of 0.01 and calibrated daily with pH 2, 4, and 7 buffers. Conductivity (μS cm -

1) was measured with a YSI 30 meter with a conductivity error of 0.5%. Dissolved oxygen

(DO) was measured with a PreSens Fibox 4 Trace meter that has a detection limit of 0.94

μmol kg-1 and an error of 0.4% (Robertson, 2019).

X-ray Fluorescence measurements Four plant species and 10 replications were picked for method comparison analysis, which

are: Cannabis sativa, Artemisia ludoviciana, Triticum aestivum, and Pseudoroegnaria

spicata (Photo 3). Species were chosen depending on how well they grew in the

contaminated soil matrix, how they reacted to the introduction of groundwater, and how

many replicates survived the greenhouse experiment. Pulverized soil samples and ground

plant samples were placed into specialized sample cups designed for pXRF analysis,

covered with a Mylar film, and labeled. Soil metals analyses were carried out with a

Thermo Scientific Niton XL3t GOLDD++ model analyzer in “Test-all Geo” mode. The prepared sample cups were placed into the pXRF test stand and tested by the remotely operated pXRF for 40 seconds each: 20 seconds in the Main Menu and 10 seconds for

Light and Low elements. A background material tested was aluminum foil.

A B C

Photo 3. Plant species chosen for analysis via pXRF and ICP-OES. A: Pseudoroegnaria spicata, B: Artemisia ludoviciana, C: Triticum aestivum, D: Cannabis sativa. Photo11 Credit: Robert Pal.

Method Comparison Analysis To test the accuracy of the pXRF, the results were compared to ICP-OES results via the

Method Comparison Regression (mcr) package in RStudio (Manuilova 2014). The Deming

method was used because it quantifies the relationship between two measurement methods;

it addresses regression errors in both variables (x- and y- axis) without repeated

measurements unlike the simple linear regression model, where the explanatory variable is

assumed to be measured without error.

To determine if the datasets are statistically similar, the US EPA standards were used to

establish data quality. R2 values greater than 0.85 meet the “definitive” quality level, and r 2

between 0.70 and 1.0 meets the “quantitative” quality level, and less than 0.70 meets the

“qualitative” quality level (US EPA 1998).

Phytoextraction Efficiency and Bioconcentration Factor Phytoextraction efficiency (PE%) (Eq. 2) looks at the total recovery of metals that plants

extract from soil (Yang et al., 2017). The mass of soil in each pot was 217.5 g, which was

calculated from the volume of the growing pots (164 mL) multiplied by the density of the

soil; the calculated mass was divided by two since the soil matrix consisted of 50% potting

soil. The density of the soil from the study area was determined by Tucci (2014), and the

alluvial sand has a density of 2655 kg m-3.

−1 퐶푚푒푡푎푙 푐표푛푐푒푛푡푟푎푡𝑖표푛 𝑖푛 푝푙푎푛푡 (푚푔 푘푔 ) × 푊푝푙푎푛푡 푑푟푦 푤푒𝑖𝑔ℎ푡 (푔) 푃퐸 (%) = −1 × 100% 퐶푚푒푡푎푙 푐표푛푐푒푛푡푟푎푡𝑖표푛 𝑖푛 푠표𝑖푙 (푚푔 푘푔 ) × (217.5 푔 ) (Eq. 2)

It is typical to implement bioconcentration factors (BCF) (Eq. 3) when looking at the

phytoextraction efficiency of species. BCF looks at the plants ability to accumulate from

12 the contaminated substrate (Wu et al., 2011). When plants have a bioconcentration factor of less than 1 it is assumed that this plant is not feasible for phytoextraction; however, it has been demonstrated that some species when grown on contaminated soils show great phytoextraction potential with bioconcentration factors less than 0.2 (McGrath & Zhao,

2003).

퐶 (푚푔 푘푔−1) 푐표푛푐푒푛푡푟푎푡𝑖표푛 𝑖푛 푝푙푎푛푡푠 (Eq. 3) 퐵퐶퐹 = −1 퐶푐표푛푐푒푛푡푟푎푡𝑖표푛 𝑖푛 푠표𝑖푙 (푚푔 푘푔 )

To compare PE% and BCF between species to understand “how many times greater” each species was to each other, the average of Cannabis sativa was divided by the average of each species. Cannabis sativa was chosen due to it being a hyperaccumulator and the only non-native test species.

Plant Species Metal(loid) Tolerance A Kruskal-Wallis H test was used to understand how the tolerance to each contaminant compares between species. This is a rank-based nonparametric test that is used to determine if there is statistical difference between groups and does not assume the data variation is normal. The post-hoc Tukey Test was implemented on each species to determine if any species are statistically different (p-value <0.05). A result of ‘Do Not

Test’ (DNT) occurs for a comparison when no significance difference is found between two means that enclose that comparison, and should be treated as no significant difference even if there appears to be one. For example, if you had four means sorted in order, and found no difference between means 4 vs. 2, then you would not test 4 vs. 3 and 3 vs. 2, but still test 4 vs. 1 and 3 vs. 1.

RESULTS AND DISCUSSION

Groundwater and Soil Chemistry One groundwater well (GS-32S) was sampled for trace elements, major cations and anions;

In situ pH, conductivity, temperature, and dissolved oxygen were measured in the field.

165-gallons of the groundwater was stored and monitored weekly (Table 1A-D). Dissolved oxygen (DO) measurements were not collected in situ for 190924B and 190926B; the values were obtained from the “water isotope” sample vial. DO values increased from 5.77 to 7.09 mg L-1 for the vial measurements. Weekly drum measurements show a decreasing

DO value ranging from 5.52 to 0.68 mg L-1 relative to a decreasing pH.

Table 1A. Groundwater parameters for sampling well and storage. D.O. = dissolved oxygen

Sample ID Sample Name T (°C) pH Cond. (uS/cm) D.O. (mg/L) 190924B GS-32S 21 2.432 2649 5.77 190926B Drum 1 (GS-32S) 19.9 2.868 2664 7.09 191003B Drum 1 (GS-32S) 20.2 2.736 2528 5.52 191010B Drum 1 (GS-32S) 20.7 2.694 2465 2.47 191017B Drum 1 (GS-32S) 19.7 2.665 2397 0.68

Major anions (Table 1B) increased in concentration during groundwater storage except for

-2 -1 -3 -1 SO4 which decreased from 2777 to 2115 mg L , and PO4 decreased from 0.185 mg L to BDL two days after groundwater collection.

Table 1B. Major anions for the groundwater well and storage via IC. Units are in ppm; BDL = below detection limit.

- - - -2 -3 - Sample ID Sample Name F Cl Br SO4 PO4 NO3 190924B GS-32S 4.85 108 BDL 2777 0.185 1.76 190926B Drum 1 (GS-32S) 4.43 106 BDL 2696 BDL 1.92

191003B Drum 1 (GS-32S) 5.54 113 0.088 2196 BDL 2.54

191010B Drum 1 (GS-32S) 5.49 112 0.084 2198 BDL 2.52 191017B Drum 1 (GS-32S) 5.35 112 0.086 2115 BDL 2.48

Major cations were relatively stable for the extent of groundwater storage except for: Ca+2

where the exhibited behavior shows depletion, K+ shows slight enrichment within the first

two days and depletion during storage, and both Na+ and Mg+2 show depletion (Table 1C).

Table 1C. Major cations for the groundwater well and storage via IC. Units are in ppm; BDL = below detection limit.

Sample ID Sample Name Li+ Na+ K+ Mg+2 Ca+2

190924B GS-32S 0.324 61.4 5.66 88.4 396

190926B Drum 1 (GS-32S) 0.317 61.4 6.41 85.6 380 191003B Drum 1 (GS-32S) 0.322 58.7 6.38 85.1 377 191010B Drum 1 (GS-32S) 0.326 58.1 6.20 84.8 376 191017B Drum 1 (GS-32S) 0.326 58.1 6.34 85.7 379

Contaminants of concern were analyzed via ICP-OES since the concentrations were above

the upper detection limit for ICP-MS; Arsenic is the only exception and was analyzed via

ICP-MS. Throughout the groundwater storage, Mn and Cd did not show depletion or

enrichment unlike the depletion of Fe, Cu, Zn, and As observed (Table 1D).

Table 1D. Contaminants of concern concentrations for the groundwater well and storage via ICP-OES in ppm. As was analyzed via ICP-MS and is in ppb. BDL = below detection limit.

Sample ID Sample Name Mn Fe Cu Zn As Cd Pb 190924A Blank BDL BDL BDL BDL BDL BDL BDL 190924B GS-32S 20.8 122 120 100 793 0.475 BDL 190926B Drum 1 (GS-32S) 19.4 102 110 92.6 304 0.442 0.196 191003B Drum 1 (GS-32S) 20.5 81.4 110 80.0 105 0.424 0.210 191010B Drum 1 (GS-32S) 20.4 74.1 111 80.0 66.3 0.415 BDL 191017B Drum 1 (GS-32S) 20.5 73.1 112 80.8 58.6 0.422 0.192

Soil was collected from three distinctive layers (Photo 4) to be analyzed for bulk chemistry with pXRF and prepared for ICP-OES analysis via acid digestions (Table 2).

Photo 4. Wall of the soil pit showing the three layers collected for analysis. Yellow lines represent boundary lines between the organic, clay, and alluvial sandy loam.

Table 2. Soil digested mass and contaminants of concern concentrations analyzed via ICP- OES. Units are in ppm. Sample Name Mass (g) As Cu Fe Mn Pb Zn Soil 1 0.5127 137 1281 22411 351 466 2417 Soil 2 0.5842 283 293 29065 196 364 2783 Soil 3 0.421 382 289 27292 167 324 1418

Changing Groundwater Chemistry The lowest pH value seen in sample 190924B, which was measured at the time of sampling, is hypothesized to be a result of not purging enough volume of water out of the well. Groundwater concentrations for contaminants of concern did not change with storage except for Fe, Zn, and As which show depletion (Figure 3). pH is the dominating factor for arsenic examined in groundwater; at higher pH it is expected to have higher concentrations

Figure 3. Changing groundwater concentrations. Note two y-axis; sample names year/month/day. Data for GS-32S (2010) was obtained from Montana’s GWIC database. of As (Katsoyiannis & Katsoyiannis 2006).

Ferrous iron concentrations decreased from 0.12 mg L-1 to BDL from the precipitation of

+3 jarosite (KFe 3(OH)6(SO4)2) or schwertmannite (Fe8O8(OH)6(SO4) · nH2O). this

2- precipitation was the likely source of the decrease in SO4 concentrations observed (Figure

+ -2 4). NH4 and S both have a significant increase two weeks after groundwater collection on 191010B. It is unlikely microbial activity induced the enrichment due to the D.O.

+ -2 -2 - Figure 4. Field spectrophotometry for NH4 and S . SO4 and NO3 concentrations measured via ICP-OES. Note that each y-axis has a different scale.

18 concentration being above 0.5 mg L-1, and microbial samples for this week are stored at -80

°C.

Plant Growth Weekly growth measurements were made for each plant species. All plant species show no difference between treatment groups during the growing phase. Once plants transitioned to the stationary phase, treatment groups with mycorrhizae are showing increased growth, where non-mycorrhizae groups show either a decrease or increase in growth (Figure 5).

Once groundwater was implemented, Cannabis sativa and the grasses were either in the stationary phase (Figure 5A and D) or dying (Figure 5C). This is likely a result of the species being at the growing capacity for the growing pots. There was no evidence of the grasses dying or a negative impact on their health (i.e. discoloration, loss of chlorophyll, loss of biomass). Cannabis sativa was dying; there was loss of biomass and discoloration in the leaves. Artemisia ludoviciana was the only species used for analysis that was still in the growing phase after groundwater implementation (Figure 5B)

Plant growth rates were calculated by taking the natural log of each treatment group’s average and determining the slope of the line, which is the growth rate (Figure 6A). The fastest growing plants species are the grasses which include wheat, basin wildrye, and bluebunch wheatgrass; one grass, tufted hairgrass, did not grow as fast. Mycorrhizae appears to have not influenced the growth rate of most of the plant species. The tree species, quaking aspen, and the sub-shrub (between a shrub and a wildflower, steams are woody) species, hairy goldenaster, both have the lowest growth rates besides giant goldenrod which did not germinate. The remaining forbs and shrubs have similar growth rates with variability coming from number of germinated seeds except for rubber rabbitbrush and Holbøll's rockcress, which are slow growers in the soil conditions. 19

Post groundwater implementation saw the opposite; plants that had a higher growth rate prior resulted in having a lower rate once groundwater was implemented (Figure 6b). Hemp is categorized as a forb, and compared to other forbs, the growth rate was at least double on contaminated soils.

Due to growth rates inhibited by the contamination present, most of the plant species did not have a long enough root system to reach the inoculated layer of mycorrhizal fungi, with the exception for the grass species and Cannabis sativa. Post-groundwater introduction

(day 56) groups show an increased growth with mycorrhizae, with the groundwater treatment groups having the greatest increase. Two primary sources of this observation are:

+ (1) the death of a replicate or (2) due to the high concentration of NH4 and other nutrients in the groundwater. Plant species replicate deaths did occur, but the cause is most likely due to the heavy metal(loid) concentrations in the groundwater and soil. The abundance of nutrients from the groundwater most likely induced increased growth, whether the mycorrhizal fungi was accepted by the host plant. Even though Artemisia ludoviciana was still in the growing phase post-groundwater, the growth rate decreased from an average of

0.478 mm day-1 to 0.143 mm day-1 (Figure 6A-B), and was showing no signs of decreased plant health.

Figure 5. Plant growth during the greenhouse experiment. A: Triticum aestivum; B: Artemisia ludoviciana; C: Cannabis sativa; D: Pseudoroegnaria spicata. Each data point represents the average plant length for each treatment group, with error bars representing the standard deviation. Vertical dashed line represents when groundwater was implemented.

Figure 6. Plant growth rates. A: Pre-GW and B: Post-GW. Plant labels are the abbreviated scientific names of each species with the exception for wheat and hemp. Descae = tufted hairgrass; Gairi = blanketflower; Artlud = white sagebrush; Poptre = quaking aspen; Arttri = big sagebrush; Helann = common sunflower; Boehol = Holbøll's rockcress; Lupser = Pursh’s silky lupine; Leycin = basin wildrye; Psespi = bluebunch wheatgrass; Hetvil = hairy goldenaster; Erinau = rubber rabbitbrush. A = Grasses; B = Forbs; C = Sub-shrub; D = shrub; E = tree.

Plant Species Tolerance to the Present Metal(loids) To understand each species ability to withstand and adapt to the higher concentrations of toxic metal(loid)s found, a Kruskal-Wallis H test was conducted between each species and metal(loid) of concern. Among all plants, Cannabis sativa and Artemisia ludoviciana had the highest tolerance for all metals while Triticum aestivum showed moderate tolerance and

Pseudoroegneria spicata had the lowest.

Copper Cannabis sativa compared to Pseudoroegneria spicata and Triticum aestivum showed a significantly higher level of Cu tolerance at p-value (P)=0.016 and P=0.028, respectively

(Table 3). Comparing Cannabis sativa to Artemisia ludoviciana and Artemisia ludoviciana to Pseudoroegneria spicata showed no significant difference at P=0.211 and P=0.643, respectively. ‘Do Not Test’ occurred for Artemisia ludoviciana to Triticum aestivum and

Triticum aestivum to Pseudoroegneria spicata.

Table 3. Kruskal-Wallis H test results on Cu. DNT = Do Not Test

Comparison Difference of Means P P<0.05 Hemp vs Psespi 187.9 0.016 Yes Hemp vs Wheat 174.0 0.028 Yes Hemp vs Artlud 117.9 0.211 No Artlud vs Psespi 70.0 0.643 No Artlud vs Wheat 56.1 0.780 DNT Wheat vs Psespi 13.9 0.995 DNT

For copper tolerance, Cannabis sativa showed the highest tolerance and Artemisia ludoviciana was moderately tolerant (Figure 7). Artemisia ludoviciana and Triticum aestivum overlapped at low concentrations and showed to be the least tolerable.

Manganese As for Manganese levels in the test plants, Artemisia ludoviciana compared to Triticum aestivum and Pseudoroegneria spicata shows significant difference with P=0.007 and

P=0.010, respectively. Cannabis sativa showed no significance between Artemisia ludoviciana and Triticum aestivum with P=0.813 and P=0.063, respectively. ‘Do Not Test’ occurred when comparing Pseudoroegneria spicata to Cannabis sativa and

Pseudoroegneria spicata meaning there is no difference (Table 4).

Table 4. Kruskal-Wallis H test results on Mn. DNT = Do Not Test

Comparison Difference of Means P P<0.05 Artlud vs. Wheat 296.30 0.007 Yes Artlud vs. Psespi 286.5 0.010 Yes Artlud vs. Hemp 75.400 0.813 No Hemp vs. Wheat 220.90 0.063 No Hemp vs. Psespi 211.10 0.081 DNT Psespi vs. Wheat 9.80 1.000 DNT

For manganese tolerance, Artemisia ludoviciana was the most tolerable with Cannabis sativa; both overlap within their respective 95% confidence interval. Triticum aestivum and

Pseudoroegneria spicata show the least tolerance and overlap at lower concentrations

(Figure 7).

Iron, Lead, and Zinc The differences in median values among plant species were not great enough to deduce whether the variation is due to random sampling variability; therefore, there is not a statistically significant difference between species for Fe, Pb, and Zn with a P=0.079,

P=0.176, and P=0.260, respectively.

For iron, species concentrations overlap at all levels meaning that there is not a specific species that shows better tolerance (Figure 7). Fe and Zn are both a required micronutrient for growth and reproduction, so it is expected to see similar tolerance between species.

Lead was not detectable in all plant replicates from the ICP-OES.

Figure 7. Plant species tolerance to metals of concern. The vertical line within the box represents the difference of means, circles indicate outliers, and error bars represent the 95% confidence interval. Arsenic was excluded due to being below detection limit from ICP-OES. 26

Phytoextraction Efficiency and Bioconcentration Factor The average phytoextraction efficiency (PE%) and bioconcentration factor (BCF) of

Cannabis sativa was compared to each test species since Cannabis sativa showed the greatest metal(loid) tolerance (Table 5A-B); raw PE% and BCF values are summarized in

Appendix A.

The average phytoextraction efficiency (PE%) of hemp was 3-8 times higher compared to the other test plants in the case of copper, 1-4 times higher for Fe, 1-2 times higher for Mn,

4-15 times higher for Pb, and 11-20 times higher in the case of Zn (Table 5A).

Table 5A. Comparing the average PE% of Cannabis sativa to each test plant.

Species Cu Fe Mn Pb Zn Artemisia ludoviciana 6 4 1 15 19 Pseudoroegneria spicata 8 4 2 11 20 Triticum aestivum 3 1 1 4 11

The average bioconcentration factor (BCF) of Cannabis sativa was 2-6 times higher compared to the other test species for Cu, 2-3 times higher for Fe, 1-3 times higher for Mn,

4-6 times higher for Pb, and 4-11 times higher in the case of Zn (Table 5B).

Table 5B. Comparing the average BCF of Cannabis sativa to each test plant. Species Cu Fe Mn Pb Zn Artemisia ludoviciana 2 2 1 4 4 Pseudoroegneria spicata 6 3 3 6 10 Triticum aestivum 4 2 3 4 11

Plant tolerance of Cu differed significantly for Cannabis sativa when compared to

Pseudoroegneria spicata and Triticum aestivum, but the PE% between species was 8 and 3 times higher, respectively. Artemisia ludoviciana and Triticum aestivum show no statistical difference between total recovery, and Artemisia ludoviciana shows no significant difference with its ability to accumulate compared to Cannabis sativa. Artemisia ludoviciana showed similar metal tolerance to Cannabis sativa while the PE% was 6 times lower. When looking at the ability to accumulate Cu from the contaminated soil, Artemisia ludoviciana and Triticum aestivum should, respectively, accumulate 2 and 4 times less than

Cannabis sativa; however, Triticum aestivum exceeded expectations by recovering 3 times less than Cannabis sativa, and Artemisia ludoviciana underperformed and recovered 6 times less than Cannabis sativa. Even though Cannabis sativa and Artemisia ludoviciana both have the best Cu tolerance, Triticum aestivum shows the most similar recovery of Cu from the contaminated soil.

There is no significant difference between Mn and Zn tolerance comparing Cannabis sativa to Artemisia ludoviciana, Pseudoroegneria spicata, and Triticum aestivum. However,

Artemisia ludoviciana is a sub-shrub and shows significant difference of metal tolerance between the two grasses Pseudoroegneria spicata and Triticum aestivum, but not Cannabis sativa, which is a forb. Cannabis sativa can accumulate 3 times more Mn than the grasses, and Artemisia ludoviciana is able to accumulate the same as Cannabis sativa. Triticum aestivum performed better than expected by recovering the same as Cannabis sativa and

Atemisia ludoviciana when it should have recovered 3 times less. When looking at the ability to accumulate Zn, Cannabis sativa should accumulate 4 and 11 times more than

Artemisia ludoviciana and Triticum aestivum, respectively. Triticum aestivum recovered

28 what was expected, but Artemisia ludoviciana underperformed by recovering 19 times less

Zn than Cannabis sativa.

Artemisia ludoviciana did not transition to a stationary phase meaning that the species was still growing by the end of the greenhouse portion; this might have had an influence on the

PE% and BCF. Therefore, if time in the greenhouse was extended for species still growing during groundwater implementation it would be expected to see Artemisia ludoviciana with similar or greater metal(loid) tolerance, PE%, and BCF than Cannabis sativa, which is a hyperaccumulator.

Comparing the Outcomes of pXRF and ICP-OES Analyses The pXRF overreported all contaminants 1 to 10 times more than the ICP-OES analysis with the exception for a few samples close to 1:1 and 100:1 (Figure 8).

Figure 8. Method comparison of metal concentrations determined by pXRF and by ICP- OES for all plant samples. Dashed lines represent ratios between the two.

Looking at individual species (Figure 9A-D), Pseudoroegnaria spicata shows the least variability in precision for concentrations unlike Artemisia ludoviciana, Cannabis sativa, and Triticum aestivum. There was no statistical difference found between treatment groups for each individual species.

Figure 9. ICP-OES and pXRF concentrations for each plant species. Dashed lines represent ratios between the two. A: Artemisia ludoviciana; B: Cannabis sativa; C: Pseudoroegnaria spicata; D: Triticum aestivum

To test the accuracy of the pXRF, the results were compared to ICP-OES results via a

Deming regression in the Method Comparison Regression (mcr) package in RStudio, and the quality of data was determined by following the US EPA data quality guidelines

(Manuilova 2014).

Zn and Pb had r2 values of 0.868 and 0.917 respectively (Figure 10) which meet the US

EPA standards of definitive data quality level, and agrees with the findings of Trilling

(2018) besides Cu; however the number of observations for the Pb analysis was 19, and each other analysis had 40 with the exception of As. Arsenic, Cu, Mn, and Fe had r2 values of 0.599, 0.521, 0.622, and 0.520, respectively, which is at the “qualitative” data quality level meaning that the datasets are statistically different.

Figure 10. Deming regression analysis of pXRF against ICP-OES analysis. Deming relationship (solid blue line) and confidence intervals (dashed blue line) are shown on each plot; data is in units of mg kg -1.

CONCLUSION Decades of mining in Butte, MT has left a detrimental impact on the soil and groundwater quality within the community. We have demonstrated that plants will germinate and grow in a soil matrix of 50% contaminated soil and 50% potting soil but will have inhibited health and growth in 100% contaminated soil. The shallow alluvial aquifer will provide an abundance of needed nutrients to the plants. Cannabis sativa and Artemisia ludoviciana were the most tolerable to the heavy metals and metalloids present and both have great potential for use in remedial purposes. Future research on this topic should re-examine the greenhouse portion and implement the groundwater at the start or extend the length of groundwater treatment to provide the species with more time to extract and accumulate the contaminants, and also compare the results to a field experiment; comparing metal(loid) concentrations found in stems/leaves to the roots would help understand how the contamination is inhibiting the growth of the root system; a metagenomic survey of the soil, groundwater, and samples of the stored groundwater would allow us to understand what ecological interactions are happening on the microbial level. Further research on how the contamination impacted the quality of hemp fiber would be useful because it is important to understand how hemp fiber quality will be influenced when used concurrently for phytoremediation and industrial manufacturing purposes.

ACKNOWLEDGMENTS A special thank you my advisors Dr. Chris Gammons and Dr. Robert Pal, and my committee member Dr. Katie Hailer for their immense help with laboratory work and writing. I would like to thank the Farmers Union Industries Foundation and Farmers

Education and COOP Union, Sigma Xi Grants in Aid of Research, and the Society of

Ecological Restoration Northwest for funding this project. I would also like to thank

Krystal Weilage and the Native Plant Program for immense help during the greenhouse portion; Gary Icopini and Steve McGrath for groundwater collection, and Jackie Timmer and Ashley Huft for sample analyses from the Montana Bureau of Mines and Geology;

Kyle Nacey and Caleb Lockyer for soil collection.

REFERENCES

Ali, H., Khan, E., & Sajad, M. A. (2013). Phytoremediation of heavy metals—concepts and applications. Chemosphere, 91(7), 869-881.

Brooks, M. L., D'antonio, C. M., Richardson, D. M., Grace, J. B., Kee ley, J. E., DiTomaso, J.M. & Pyke, D. (2004). Effects of invasive alien plants on fire regimes. AIBS Bulletin, 54(7), 677-688.

Charles, H., & Dukes, J. S. (2008). Impacts of invasive species on ecosystem services. In Biological Invasions (pp. 217- 237). Springer, Berlin, Heidelberg.

Crooks, J. A. (2002). Characterizing ecosystem‐level consequences of biological invasions: the role of ecosystem engineers. Oikos, 97(2), 153-166.

Daehler, C. C. (2003). Performance comparisons of co-occurring native and alien invasive plants: implications for conservation and restoration. Annual Review of Ecology, Evolution, and Systematics, 34(1), 183-211.

Environmental Protection Agency (2006). Record of Decision, Butte Priority Soils Operable Unit, Silver Bow Creek/Butte Area NPL Site, Butte Montana, Lead Agency: US EPA Region VIII, September 2006.

Katsoyiannis, I. A., & Katsoyiannis, A. A. (2006). Arsenic and other metal contamination of groundwaters in the industrial area of Thessaloniki, Northern Greece. Environmental Monitoring and Assessment, 123(1-3), 393-406.

Marietou, A. (2016). Nitrate reduction in sulfate-reducing bacteria. FEMS Microbiology Letters, 363(15), fnw155.

McGrath, S. P., & Zhao, F. J. (2003). Phytoextraction of metals and metalloids from contaminated soils. Current Opinion in Biotechnology, 14(3), 277–282.

Michalski, R., Jabłonska, M., Szopa, S., & Łyko, A. (2011). Application of ion chromatography with ICP- MS or MS detection to the determination of selected halides and metal/metalloids species. Critical Reviews in Analytical Chemistry, 41(2), 133-150.

Oliveira, S. R., Neto, J. A. G., Nóbrega, J. A., & Jones, B. T. (2010). Determination of macro- and micronutrients in plant leaves by high-resolution continuum source flame atomic absorption spectrometry combining instrumental and sample preparation strategies. Spectrochimica Acta Part B: Atomic Spectroscopy, 65(4), 316-320.

Quoreshi, A. M. (2008). The use of mycorrhizal biotechnology in restoration of disturbed ecosystem. In Mycorrhizae: Sustainable Agriculture and Forestry (pp. 303-320). Springer, Dordrecht. Pal, R. & Carpenter, N. (2020) Weed flora of hemp fields in west-central Montana. Farmers Union Industries Foundation. 29, 6-7.

Roberston, I. 2019. Limitations to photosynthesis in Silver Bow and Blacktail creeks. Masters Thesis, Montana Technological University, Butte, Montana.

Rúa, M. A., Antoninka, A., Antunes, P. M., Chaudhary, V. B., Gehring, C., Lamit, L. J. & Lajeunesse, M. J. (2016). Home-field advantage? Evidence of local adaptation among plants, soil, and arbuscular mycorrhizal fungi through meta- analysis. BMC Evolutionary Biology, 16(1), 122.

Tucci, N. J., & Icopini, G. A. (2012). Geochemical and hydrogeologic investigation of groundwater impacted by wastes left in place in the Butte Priority Soils Operable Unit Butte, MT. Montana Bureau of Mines and Geology, Open File 613, 198 p.

Tucci, N. J. (2014). Tailings/Impacted Sediment Delineation of the Diggings East, Blacktail Creek Berm, and Northside Tailings Areas. Natural Resources Damage Program. Butte, MT.

U.S. Environmental Protection Agency (1998) Environmental Technology Verification Report Field Portable X-ray Fluorescence Analyzer

Wu, Q., Wang, S., Thangavel, P., Li, Q., Zheng, H., Bai, J., & Qiu, R. (2011). Phytostabilization potential of Jatropha curcas L. International Journal of phytoremediation, 13(8), 788-804.

Yang, Y., Ge, Y., Zeng, H., Zhou, X., Peng, L., & Zeng, Q. (2017). Phytoextraction of cadmium-contaminated soil and potential of regenerated tobacco biomass for recovery of cadmium. Scientific reports, 7(1), 7210.

APPENDIX

Table 3. pXRF data for replicates used in analysis; units are in ppm. BDL = below detection limit

Sample As Cu Fe Mn Pb Zn Artlud 9 26 226 2012 689 BDL 1630 Artlud 12 51 844 5137 3123 26 5546 Artlud 13 29 581 4297 2624 21 4105 Artlud 14 32 555 2840 2100 BDL 5778 Artlud 15 44 751 6737 2130 39 5240 Artlud 17 19 763 3516 1622 21 4205 Artlud 25 37 351 3955 1504 23 1839 Artlud 28 26 291 3199 1550 15 2680 Artlud 37 17 373 1578 1913 BDL 2756 Artlud 39 24 297 1920 1906 BDL 2122 Hemp 2 51 799 10654 1586 43 2833 Hemp 3 54 528 3174 1681 BDL 3425 Hemp 10 69 587 11738 1838 24 2964 Hemp 16 83 929 6156 2361 58 4620 Hemp 18 86 958 3289 3222 31 4658 Hemp 28 132 944 9168 522 163 19966 Hemp 29 124 1493 11982 1349 77 9134 Hemp 34 87 744 9498 1749 52 4391 Hemp 36 165 759 3284 1811 BDL 6780 Hemp 39 70 738 4257 1603 22 6303 Psespi 1 25 240 3779 752 20 1676 Psespi 4 31 256 2807 520 BDL 1833 Psespi 14 19 349 3591 771 15 2089 Psespi 16 17 335 2154 488 BDL 2078 Psespi 31 28 317 2265 604 BDL 2327 Psespi 32 27 345 3535 476 15 2327 Psespi 33 23 332 3662 629 BDL 2940 Psespi 35 32 532 4544 1616 BDL 2260 Psespi 38 20 333 3329 948 21 2552 Psespi 39 23 411 4058 747 17 2347 Wheat 1 15 289 1664 510 BDL 1001 Wheat 3 19 256 1901 919 BDL 1105 Wheat 4 BDL 340 2282 465 BDL 591 Wheat 16 16 304 2788 607 BDL 2549 Wheat 17 19 291 3119 433 13 2118 Wheat 18 23 286 4194 537 13 2515 Wheat 19 24 288 5515 676 11 2551 Wheat 21 16 211 2280 536 14 1151 Wheat 23 16 246 3076 285 15 1588 Wheat 39 17 288 2562 825 BDL 2407

Table 4. Average pXRF for Artemisia ludoviciana; units are in ppm. NA = not measured

Sample As Cu Fe Mn Pb Zn Artlud 1 14 94 599 258 16 404 Artlud 3 10 73 323 103 NA 187 Artlud 5 9 74 356 145 NA 365 Artlud 6 12 73 447 170 6 457 Artlud 7 10 232 522 158 11 450 Artlud 8 NA 44 712 NA 164 155 Artlud 9 26 226 2012 689 NA 1630 Artlud 12 51 844 5137 3123 26 5546 Artlud 13 29 581 4297 2624 21 4105 Artlud 14 32 555 2840 2100 NA 5778 Artlud 15 44 751 6737 2130 39 5240 Artlud 17 19 763 3516 1622 21 4205 Artlud 19 14 317 1831 1692 NA 2880 Artlud 20 23 712 3098 1112 NA 3532 Artlud 22 19 293 2517 452 NA 1220 Artlud 23 17 246 1841 634 NA 1510 Artlud 24 26 313 1970 641 NA 1283 Artlud 25 37 351 3955 1504 23 1839 Artlud 27 24 230 2147 615 12 1268 Artlud 28 26 291 3199 1550 15 2680 Artlud 29 19 260 2219 915 NA 1582 Artlud 32 21 346 1796 1362 NA 2824 Artlud 33 22 475 1977 1504 NA 2399 Artlud 34 14 270 1877 1041 NA 1640 Artlud 35 17 313 1781 772 NA 1684 Artlud 37 17 373 1578 1913 NA 2756 Artlud 39 24 297 1920 1906 NA 2122 Artlud 40 17 387 2455 962 NA 2569

Table 5. Average pXRF data for Cannabis sativa; units are in ppm. NA = not measured

Sample As Cu Fe Mn Pb Zn Hemp 2 51 799 10654 1586 43 2833 Hemp 3 54 528 3174 1681 NA 3425 Hemp 6 66 369 2694 2455 NA 2344 Hemp 10 69 587 11738 1838 24 2964 Hemp 11 57 546 2577 467 NA 2719 Hemp 12 21 441 2978 1485 NA 1651 Hemp 13 43 702 3892 1467 18 3735 Hemp 14 36 309 2853 862 NA 2517 Hemp 16 83 929 6156 2361 58 4620 Hemp 17 65 719 6614 1273 59 3280 Hemp 18 86 958 3289 3222 31 4658 Hemp 21 47 565 11369 1021 26 2023 Hemp 23 47 343 3141 1119 29 1860 Hemp 25 65 741 4096 1114 39 4252 Hemp 27 22 309 2606 1284 NA 1804 Hemp 28 132 944 9168 522 163 19966 Hemp 29 124 1493 11982 1349 77 9134 Hemp 30 76 446 6845 1103 24 3125 Hemp 33 40 604 4258 1478 21 4853 Hemp 34 87 744 9498 1749 52 4391 Hemp 35 72 534 2963 1548 NA 3294 Hemp 36 165 759 3284 1811 NA 6780 Hemp 37 100 811 8946 1343 36 3225 Hemp 38 31 393 3308 1101 14 1971 Hemp 39 70 738 4257 1603 22 6303 Hemp 2 51 799 10654 1586 43 2833 Hemp 3 54 528 3174 1681 NA 3425 Hemp 6 66 369 2694 2455 NA 2344

Table 6. Average pXRF data for Pseudoroegnaria spicata; units are in ppm. NA = not measured

Sample As Cu Fe Mn Pb Zn Psespi 1 25 240 3779 3779 20 1676 Psespi 2 15 138 892 892 7 865 Psespi 3 15 162 1608 1608 NA 1398 Psespi 4 31 256 2807 2807 NA 1833 Psespi 6 18 219 2153 2153 NA 2624 Psespi 8 22 225 2614 2614 NA 1402 Psespi 10 18 183 2367 2367 NA 1287 Psespi 14 19 349 3591 3591 15 2089 Psespi 15 18 308 2814 2814 NA 1993 Psespi 16 17 335 2154 2154 NA 2078 Psespi 17 13 249 1618 1618 NA 1613 Psespi 18 14 311 2087 2087 NA 1998 Psespi 19 17 372 2552 2552 NA 1955 Psespi 20 18 347 2440 2440 NA 1788 Psespi 21 19 207 2192 2192 14 1603 Psespi 22 19 225 2256 2256 13 1206 Psespi 23 17 206 2031 2031 NA 1346 Psespi 24 30 255 2482 2482 NA 1838 Psespi 27 17 219 2606 2606 NA 1301 Psespi 28 20 219 2758 2758 12 952 Psespi 29 21 270 2537 2537 NA 1387 Psespi 31 28 317 2265 2265 NA 2327 Psespi 32 27 345 3535 3535 15 2327 Psespi 33 23 332 3662 3662 NA 2940 Psespi 35 32 532 4544 4544 NA 2260 Psespi 38 20 333 3329 3329 21 2552 Psespi 39 23 411 4058 4058 17 2347 Psespi 40 16 237 2025 2025 NA 1814

Table 7. Table 6. Average pXRF data for Triticum aestivum; units are in ppm. NA = not measured

Sample As Cu Fe Mn Pb Zn Wheat 1 15 289 1664 510 NA 1001 Wheat 3 19 256 1901 919 NA 1105 Wheat 4 NA 340 2282 465 NA 591 Wheat 5 10 123 552 181 NA 690 Wheat 6 12 102 826 158 NA 999 Wheat 7 11 191 1295 568 NA 955 Wheat 8 12 172 1195 247 NA 1339 Wheat 11 11 217 1663 546 NA 1863 Wheat 12 14 252 2191 549 NA 1435 Wheat 15 13 241 1396 686 NA 2872 Wheat 16 16 304 2788 607 NA 2549 Wheat 17 19 291 3119 433 13 2118 Wheat 18 23 286 4194 537 13 2515 Wheat 19 24 288 5515 676 11 2551 Wheat 21 16 211 2280 536 14 1151 Wheat 23 16 246 3076 285 15 1588 Wheat 24 14 196 2251 188 15 1081 Wheat 25 13 173 1154 368 NA 1500 Wheat 26 16 217 1473 419 NA 1746 Wheat 29 13 180 1021 377 1038 Wheat 30 11 219 1469 320 1365 Wheat 31 9 189 985 227 929 Wheat 32 15 271 2014 458 893 Wheat 33 10 240 1754 227 1245 Wheat 34 134 1265 626 Wheat 37 21 241 3353 154 11 1251 Wheat 38 14 300 1980 159 1080 Wheat 39 17 288 2562 825 2407

Table 8. Corrected ICP-OES concentrations. Units in mg kg-1. Blank cells = not measured Sample Mass (g) As Cu Fe Mn Pb Zn Artlud 9 0.2578 46 282 166 6 401 Artlud 12 0.098 101 413 227 817 Artlud 13 0.0352 342 1594 1440 27 3264 Artlud 14 0.0611 120 485 374 1478 Artlud 15 0.0791 120 569 301 10 1362 Artlud 17 0.0322 130 412 274 978 Artlud 25 0.1552 60 549 265 14 439 Artlud 28 0.1432 41 365 260 9 664 Artlud 37 0.1788 76 232 421 773 Artlud 39 0.2622 60 259 346 5 535 Hemp 2 0.0657 73 332 383 758 Hemp 3 0.1695 97 308 396 5 913 Hemp 10 0.14 25 105 1939 373 15 688 Hemp 16 0.0165 168 356 467 1358 Hemp 18 0.0578 173 316 322 1360 Hemp 28 0.4802 289 912 2499 269 218 35610 Hemp 29 0.1654 25 198 762 185 19 1565 Hemp 34 0.201 28 164 1300 379 24 1507 Hemp 36 0.0519 249 1017 294 20 1486 Hemp 39 0.1392 35 136 694 252 13 1642 Psespi 1 0.1578 29 386 134 8 361 Psespi 4 0.3175 10 36 309 111 5 471 Psespi 14 0.1913 42 321 112 7 496 Psespi 16 0.2604 44 243 127 4 474 Psespi 31 0.1576 39 228 124 5 482 Psespi 32 0.1853 39 337 86 7 427 Psespi 33 0.2273 49 414 124 7 653 Psespi 35 0.0466 35 265 148 514 Psespi 38 0.1395 35 265 131 6 477 Psespi 39 0.1914 48 357 112 7 462 Wheat 1 0.3819 33 247 119 5 452 Wheat 3 0.488 17 124 145 2 416 Wheat 4 0.5109 7 26 28 82 Wheat 16 0.4621 51 394 136 7 562 Wheat 17 0.2874 61 1065 121 13 445 Wheat 18 0.409 35 306 123 5 488 Wheat 19 0.4835 37 351 126 7 546 Wheat 21 0.3734 10 100 668 108 9 227 Wheat 23 0.5071 32 35 822 76 7 405 Wheat 39 0.146 159 1484 129 32 643

Table 9. Uncorrected ICP-OES concentrations. Units are in mg L-1. Bold numbers = below detection limit Sample As Cu Fe Mn Pb Zn Artlud 9 0.1 0.398 2.42 1.43 0.0487 3.45 Artlud 12 0.1 0.329 1.35 0.741 0.0237 2.67 Artlud 13 0.1 0.401 1.87 1.69 0.0318 3.83 Artlud 14 0.1 0.244 0.987 0.762 0.0237 3.01 Artlud 15 0.1 0.317 1.50 0.793 0.0257 3.59 Artlud 17 0.1 0.139 0.442 0.294 0.0237 1.05 Artlud 25 0.1 0.308 2.84 1.37 0.0711 2.27 Artlud 28 0.1 0.197 1.74 1.24 0.0406 3.17 Artlud 37 0.1 0.454 1.38 2.51 0.0237 4.61 Artlud 39 0.1 0.523 2.26 3.02 0.0447 4.68 Hemp 2 0.1 0.160 0.726 0.838 0.0237 1.66 Hemp 3 0.1 0.546 1.74 2.24 0.0305 5.16 Hemp 10 0.118 0.488 9.05 1.74 0.0679 3.21 Hemp 16 0.1 0.0922 0.196 0.257 0.0237 0.747 Hemp 18 0.1 0.334 0.609 0.621 0.0237 2.62 Hemp 28 4.63 14.6 40.0 4.30 3.49 570 Hemp 29 0.137 1.09 4.20 1.02 0.104 8.63 Hemp 34 0.186 1.10 8.71 2.54 0.161 10.1 Hemp 36 0.1 0.430 1.76 0.508 0.0346 2.57 Hemp 39 0.162 0.630 3.22 1.17 0.0590 7.62 Psespi 1 0.1 0.150 2.03 0.704 0.0421 1.90 Psespi 4 0.102 0.378 3.27 1.18 0.0578 4.99 Psespi 14 0.1 0.269 2.05 0.714 0.0415 3.16 Psespi 16 0.1 0.381 2.11 1.10 0.0359 4.11 Psespi 31 0.1 0.203 1.20 0.652 0.0280 2.53 Psespi 32 0.1 0.241 2.08 0.534 0.0407 2.64 Psespi 33 0.1 0.369 3.14 0.936 0.0520 4.95 Psespi 35 0.1 0.0542 0.412 0.230 0.0237 0.799 Psespi 38 0.1 0.164 1.23 0.607 0.0299 2.22 Psespi 39 0.1 0.304 2.28 0.715 0.0460 2.95 Wheat 1 0.1 0.426 3.14 1.51 0.0636 5.75 Wheat 3 0.1 0.271 2.02 2.36 0.0262 6.76 Wheat 4 0.1 0.122 0.450 0.477 0.0237 1.40 Wheat 16 0.1 0.778 6.07 2.10 0.108 8.65 Wheat 17 0.1 0.584 10.2 1.16 0.123 4.26 Wheat 18 0.1 0.481 4.17 1.68 0.0738 6.65 Wheat 19 0.1 0.602 5.66 2.03 0.109 8.80 Wheat 21 0.122 1.24 8.31 1.34 0.116 2.83 Wheat 23 0.540 0.586 13.9 1.28 0.113 6.84 Wheat 39 0.1 0.774 7.22 0.629 0.154 3.13

Table 10. Phytoextraction potential (%) calculated from ICP-OES data. Sample Cu Fe Mn Pb Zn Artlud 9 0.019% 0.001% 0.101% 0.002% 0.017% Artlud 12 0.016% 0.001% 0.052% 0.000% 0.013% Artlud 13 0.019% 0.001% 0.119% 0.001% 0.019% Artlud 14 0.011% 0.000% 0.054% 0.000% 0.015% Artlud 15 0.015% 0.001% 0.056% 0.001% 0.018% Artlud 17 0.007% 0.000% 0.021% 0.000% 0.005% Artlud 25 0.015% 0.001% 0.096% 0.003% 0.011% Artlud 28 0.009% 0.001% 0.087% 0.002% 0.016% Artlud 37 0.021% 0.001% 0.176% 0.000% 0.023% Artlud 39 0.025% 0.001% 0.212% 0.002% 0.023% Hemp 2 0.008% 0.000% 0.059% 0.000% 0.008% Hemp 3 0.026% 0.001% 0.158% 0.001% 0.026% Hemp 10 0.023% 0.004% 0.122% 0.003% 0.016% Hemp 16 0.004% 0.000% 0.018% 0.000% 0.004% Hemp 18 0.016% 0.000% 0.044% 0.000% 0.013% Hemp 28 0.688% 0.019% 0.302% 0.132% 2.825% Hemp 29 0.051% 0.002% 0.072% 0.004% 0.043% Hemp 34 0.052% 0.004% 0.179% 0.006% 0.050% Hemp 36 0.020% 0.001% 0.036% 0.001% 0.013% Hemp 39 0.030% 0.002% 0.082% 0.002% 0.038% Psespi 1 0.007% 0.001% 0.050% 0.002% 0.009% Psespi 4 0.018% 0.002% 0.083% 0.002% 0.025% Psespi 14 0.013% 0.001% 0.050% 0.002% 0.016% Psespi 16 0.018% 0.001% 0.077% 0.001% 0.020% Psespi 31 0.010% 0.001% 0.046% 0.001% 0.013% Psespi 32 0.011% 0.001% 0.038% 0.002% 0.013% Psespi 33 0.017% 0.001% 0.066% 0.002% 0.025% Psespi 35 0.003% 0.000% 0.016% 0.000% 0.004% Psespi 38 0.008% 0.001% 0.043% 0.001% 0.011% Psespi 39 0.014% 0.001% 0.050% 0.002% 0.015% Wheat 1 0.020% 0.001% 0.106% 0.002% 0.028% Wheat 3 0.013% 0.001% 0.166% 0.001% 0.034% Wheat 4 0.006% 0.000% 0.034% 0.000% 0.007% Wheat 16 0.037% 0.003% 0.148% 0.004% 0.043% Wheat 17 0.028% 0.005% 0.082% 0.005% 0.021% Wheat 18 0.023% 0.002% 0.118% 0.003% 0.033% Wheat 19 0.028% 0.003% 0.143% 0.004% 0.044% Wheat 21 0.058% 0.004% 0.094% 0.004% 0.014% Wheat 23 0.028% 0.007% 0.090% 0.004% 0.034% Wheat 39 0.036% 0.003% 0.044% 0.006% 0.016%

Table 11. Bioconcentration factor calculated from ICP-OES data. Blanks cells = not calculated

Sample Cu Fe Mn Pb Zn Artlud 9 0.158229 0.009689 0.848304 0.015565 0.144244 Artlud 12 0.344078 0.014218 1.156353 0.293662 Artlud 13 1.167585 0.054833 7.342471 0.074439 1.172785 Artlud 14 0.409294 0.016673 1.907269 0.530991 Artlud 15 0.410742 0.019573 1.533186 0.026771 0.489193 Artlud 17 0.442431 0.014168 1.396335 0.351476 Artlud 25 0.203398 0.018887 1.349979 0.037748 0.157651 Artlud 28 0.140997 0.012542 1.324271 0.023361 0.238604 Artlud 37 0.260241 0.007966 2.146863 0.277905 Artlud 39 0.204435 0.008897 1.761459 0.014047 0.192387 Hemp 2 0.249598 0.011406 1.950639 0.272336 Hemp 3 0.330149 0.010596 2.021047 0.014827 0.328127 Hemp 10 0.357255 0.066721 1.900726 0.039963 0.247138 Hemp 16 0.572709 0.012261 2.382031 0.487977 Hemp 18 0.59225 0.010875 1.643092 0.48858 Hemp 28 3.116143 0.085977 1.369445 0.598851 12.79425 Hemp 29 0.675426 0.02621 0.943111 0.05181 0.56239 Hemp 34 0.560897 0.044727 1.932573 0.066 0.541611 Hemp 36 0.849157 0.035002 1.496906 0.054932 0.533738 Hemp 39 0.463861 0.023876 1.285419 0.034924 0.590035 Psespi 1 0.097425 0.013278 0.682282 0.021983 0.12978 Psespi 4 0.122021 0.01063 0.568377 0.015 0.169402 Psespi 14 0.14412 0.011061 0.570797 0.017875 0.178047 Psespi 16 0.149958 0.008363 0.646026 0.01136 0.170123 Psespi 31 0.132016 0.007859 0.632688 0.014639 0.173032 Psespi 32 0.133299 0.011586 0.440721 0.018098 0.153564 Psespi 33 0.166385 0.014259 0.629759 0.01885 0.23473 Psespi 35 0.119207 0.009125 0.754814 0.184809 Psespi 38 0.120491 0.009101 0.665446 0.017661 0.17153 Psespi 39 0.162786 0.012295 0.571297 0.019803 0.166128 Wheat 1 0.114326 0.008486 0.60468 0.013722 0.162286 Wheat 3 0.056916 0.004272 0.739589 0.004424 0.14931 Wheat 4 0.024474 0.000909 0.142784 0.029536 Wheat 16 0.172556 0.013558 0.694995 0.019258 0.201763 Wheat 17 0.208263 0.036632 0.617262 0.035264 0.159766 Wheat 18 0.120534 0.010523 0.62818 0.014868 0.175251 Wheat 19 0.127611 0.012083 0.642093 0.018576 0.196177 Wheat 21 0.340357 0.022971 0.548818 0.025598 0.081691 Wheat 23 0.118438 0.028292 0.386024 0.018361 0.145387 Wheat 39 0.543344 0.051042 0.658864 0.086913 0.231075

Table 12. Weekly plant growth data for Cannabis sativa. Units are in cm. DEAD = when the replication died; blank cells mean no measurement.

Sample Day 14 Day 21 Day 28 Day 35 Day 56 Day 63 Day 70 Day 77 Day 84 Hemp 1 3 5.6 6.5 7 DEAD Hemp 2 2.7 4.3 4.7 6.1 9.3 9.7 10.3 10.2 11 Hemp 3 4.1 5.7 9.6 12.1 12.2 12.6 12.6 12.7 Hemp 4 2.4 5.1 7.4 8.4 10.4 10.6 9.2 9.6 Hemp 5 2.1 4.2 5.8 6.7 Hemp 6 4.2 6.5 7.2 7.3 7.7 9.4 8 8 8 Hemp 7 3.5 5.4 5.6 5.5 DEAD Hemp 8 1.6 2.2 3.6 4.1 4.9 DEAD Hemp 9 4.1 6.6 8.1 8.3 DEAD DEAD Hemp 10 4.2 5.7 5.4 8.2 10.7 10.4 10.8 11.9 11.9 Hemp 11 3 6.4 10.5 25.6 38.7 36.6 37.7 Hemp 12 3.1 5.5 6.7 8 12 12.5 13.1 13.1 13.3 Hemp 13 2.4 5.5 7.2 11.3 15.1 15.4 16.3 16.2 16.2 Hemp 14 2.1 4.6 6.3 13.4 20.4 20.5 20.7 21.1 21.2 Hemp 15 2.9 5.4 6.8 7.5 9.1 9.1 10 10.1 9.7 Hemp 16 3.1 6.5 8.6 16.4 20.6 20.5 Hemp 17 4.1 5.6 8.9 13.4 14.2 14.4 Hemp 18 1.9 5.3 10.6 22.6 25.1 DEAD Hemp 19 2.6 5.8 9.8 21.5 24.7 DEAD Hemp 20 2.1 4.6 8.1 27.3 32.5 32.3 32.5 Hemp 21 2 5 6.9 13 19.9 21 21.3 21.1 21.3 Hemp 22 1.8 5.5 9.2 16.5 22.6 22.8 23.1 22.8 22.9 Hemp 23 1.6 4.8 6.6 11 16 16.1 16.3 16.4 16.3 Hemp 24 3.7 6 9.1 16.25 20.3 21.2 21.1 21.8 21.2 Hemp 25 3.1 5.3 8 22.5 34.8 34.8 Hemp 26 2.1 4.7 9.8 13.5 31 29.5 Hemp 27 2.1 4.4 7.6 14.8 21.7 22 22.2 22.3 21.8 Hemp 28 2.3 4.6 7.7 15.7 23.1 23.4 23.4 24.6 24.6 Hemp 29 4.8 8.2 21 42.5 42.7 42.6 Hemp 30 1.4 3.6 6.5 14.2 12.6 17.6 17.9 18 18.1 Hemp 31 2.5 6.5 8.6 18 22.5 DEAD Hemp 32 1.6 5 5.4 5.5 DEAD DEAD Hemp 33 2.4 5.3 7.3 11.3 18.8 19 19.1 19 20 Hemp 34 1.9 4 5.5 8.2 13 13.6 13.7 13.7 13.6 Hemp 35 1.4 5.5 9.7 18.1 32.1 33 32.6 Hemp 36 1.3 4 9.2 11.4 22.6 23.4 Hemp 37 3.5 5.6 12.1 41 41.7 42.1 Hemp 38 2.7 7.4 14.2 20.4 23.7 24.1 24.8 25 25.1 Hemp 39 3 6.8 11.5 26 32.5 32.2 Hemp 40 2.6 5 9.8 21.9 32.1 31.8 31.5

Table 13. Weekly plant growth data for Artemisia ludoviciana. Units are in cm. DEAD = when the replication died; blank cells mean no measurement.

Sample Day 14 Day 21 Day 28 Day 35 Day 56 Day 63 Day 70 Day 77 Day 84 Artlud 1 0.3 0.6 0.8 3.5 8.3 9.8 11.8 14.5 16.4 Artlud 2 0.4 0.7 0.8 DEAD Artlud 3 0.4 1.1 1.5 5.9 10.6 12.1 13.2 15.5 16.7 Artlud 4 0.3 0.5 0.9 1.6 5.4 6.5 8 9.6 11.7 Artlud 5 0.6 0.9 2.5 8.9 16.8 18 18.9 19.5 21.8 Artlud 6 0.4 1.1 2.3 8.6 14.7 17.5 18.2 19.7 20 Artlud 7 0.5 0.6 1.1 3.6 10.3 12.8 13.6 15.6 16.2 Artlud 8 0.6 1.2 1.9 9.6 17.5 19.2 19.7 20.7 21 Artlud 9 0.5 0.7 1.4 6.9 15.6 18.3 18.6 20.7 22.1 Artlud 10 0.4 1 1.3 7 13.4 14.9 16.8 18.5 19.6 Artlud 11 0.2 0.5 0.6 1.6 3 3.1 3.6 4 4.3 Artlud 12 0.4 0.7 1.1 3.4 8.6 10 10.1 10.5 10.6 Artlud 13 0.4 0.8 1.2 4.2 9 11.5 13.5 16 18 Artlud 14 0.5 0.6 1.1 3.3 7.1 8.4 9.2 11.2 11.9 Artlud 15 0.3 0.6 1 5 8.7 8.8 9.1 9.5 9.8 Artlud 16 0.6 0.5 0.6 DEAD Artlud 17 0.4 0.8 0.9 3.7 7.6 9.1 9 9.6 10.2 Artlud 18 0.4 1.1 0.9 1 DEAD Artlud 19 0.3 0.7 1.2 5.7 12.5 14.6 15.4 18 19.6 Artlud 20 0.4 1 1.3 5.4 7.4 8.3 8 8.1 7.7 Artlud 21 0.4 0.5 0.7 2 8.7 7.5 8.1 9.3 10.7 Artlud 22 0.3 0.6 1 5.5 12 15.6 16.2 17.6 18.5 Artlud 23 0.4 1 1.5 5.7 12.1 15.4 16.3 17.5 18.6 Artlud 24 0.4 0.8 1.1 4.9 11.3 14 15.2 16.9 18.5 Artlud 25 0.3 1 1.2 3.1 10.2 10.7 11.2 12.7 13.3 Artlud 26 0.3 0.7 0.7 1.5 4 5.3 6.4 8.1 10 Artlud 27 0.2 0.7 1.5 4.6 9.9 12 12.5 14.1 15.3 Artlud 28 0.4 0.4 1.1 2 6.1 8.7 9.1 10.2 10.7 Artlud 29 0.4 0.8 1.3 5.3 12.2 16.8 17.6 19.4 20.4 Artlud 30 0.3 0.4 0.8 1.2 3 5.2 5.6 7 8.3 Artlud 31 0.3 0.4 0.7 1.5 6.7 8.7 10.4 13.2 14.1 Artlud 32 0.3 0.5 1.1 5.5 13.6 15.4 15.6 17.9 20.7 Artlud 33 0.2 0.5 1.5 6.1 15 16.4 16.7 18.9 17.9 Artlud 34 0.4 0.7 1.4 5.3 11.7 13.8 14.6 16.6 18 Artlud 35 0.2 0.5 1.1 6.4 15.6 17.7 18.3 20.8 22.4 Artlud 36 0.4 0.6 1 4.5 11.3 12.3 14.2 17.2 18.1 Artlud 37 0.3 1 0.7 2.6 8.9 10.8 12.2 14.7 16 Artlud 38 0.2 0.8 1.5 4 13.4 12.2 13.1 15.2 17.1 Artlud 39 0.5 0.8 1.6 2 13.6 15.6 16.1 17.8 19.4 Artlud 40 0.3 0.6 1.1 4.8 10.9 12.3 13.5 16.3 18.1

Table 14. Weekly plant growth data for Triticum aestivum. Units are in cm. DEAD = when the replication died; blank cells mean no measurement. Sample Day 14 Day 21 Day 28 Day 35 Day 56 Day 63 Day 70 Day 77 Day 84 Wheat 1 5 19.8 40.9 61.1 60.6 60.3 60.1 60 Wheat 2 11.3 25.7 37.3 44.1 60.1 60 58.7 59.1 59.1 Wheat 3 20.6 32.1 33.8 37.6 45.6 44.9 44.6 44.2 43.7 Wheat 4 9.1 27.7 38.3 47.6 47.4 47 46.8 46.5 46.7 Wheat 5 21.5 35.8 42.1 48.4 55.2 54.8 54.7 54.3 54.3 Wheat 6 17 36.5 42 45.4 51.5 51 51 50.5 50.4 Wheat 7 19.4 37.4 44.2 46.7 46.8 46.5 46.4 46.4 46.3 Wheat 8 15.2 34 47.3 55 54.8 54.6 54.5 54.3 Wheat 9 4.5 21.7 33.7 39.9 49.6 50.3 50.3 50.3 49.9 Wheat 10 8.2 32.2 56.5 55.9 55.6 55.5 55.4 Wheat 11 7.5 27.3 43 43.5 43.8 43.5 43.3 Wheat 12 18.4 35.8 41 47.4 55.1 54.8 54.4 54.5 51.2 Wheat 13 14.6 30.6 40.6 49.2 53.4 54.9 58.4 54.5 55.7 Wheat 14 19.7 35.2 40.5 41.1 48.2 47.4 47.5 47.5 57.4 Wheat 15 12.9 26.9 36.8 44 54.3 53.6 54.5 54.7 54.1 Wheat 16 14.8 26.9 35 35 44.6 43.6 44.4 44.3 44.2 Wheat 17 15.1 31.8 35.8 39.2 44.1 43.6 43.9 43.2 43.3 Wheat 18 13.9 29.7 32.7 37.5 46.2 45.8 45.6 45.9 45.8 Wheat 19 12.4 27.3 35.9 47.7 41.1 43.9 41 56.7 43.4 Wheat 20 11.6 24.6 41 48 56.4 58.5 58.4 57.1 57.3 Wheat 21 10.5 22.1 34.5 44.5 51.5 50.9 51.1 50.6 50.8 Wheat 22 9 22 29 41.8 47.6 49.3 49.3 46.2 48.8 Wheat 23 12.5 26.1 35.1 45.3 54 53.2 52.9 52.5 52.4 Wheat 24 17.9 40 44.8 52.5 56.3 55.6 55.5 55.2 54.8 Wheat 25 18.5 40.5 48.2 54.5 56 52.9 53.1 52.6 52.6 Wheat 26 10 15.6 25.7 37.8 55.7 60 59.6 58.3 58.6 Wheat 27 12.5 30.8 42.7 54.6 52.2 55.9 55.7 55.5 54.3 Wheat 28 0 4.5 14.2 29 37.1 42.3 44.8 44.8 44.9 Wheat 29 17.5 35.6 45.2 50.5 60.6 59.6 59.6 59.4 59.5 Wheat 30 9.5 24.6 36.6 44.2 56.8 58.4 58.3 57.7 57.2 Wheat 31 13.9 29.8 42.5 47.5 58.1 57.3 56.5 57.1 56.3 Wheat 32 13.2 26.3 38.9 49.5 55.1 55.4 54.6 55.1 54.9 Wheat 33 23.7 45.7 49 49.5 58.1 58.2 58.1 57.6 57.8 Wheat 34 19.6 40 45.8 45.3 49.7 49.2 48.7 48.2 48.4 Wheat 35 22.8 30 41.5 41 45 44.6 44.2 43.6 43.5 Wheat 36 15 35.9 42.7 46.2 50.1 49.6 48.2 49.6 49.4 Wheat 37 21.5 31.3 34.4 39.2 42.8 42.2 42.4 41.8 41.8 Wheat 38 12.9 27.7 32.3 45.2 55.9 56.3 56.1 55.8 50.2 Wheat 39 8 12.2 18.7 33.1 54.5 53.8 53.1 53.1 53.1 Wheat 40 8.5 8.6 8.6 9 27.8 31.6 31.6 42 31.8

Table 125. Weekly plant growth data for Pseudoroegnaria spicata. Units are in cm. DEAD = when the replication died; blank cells mean no measurement. Sample Day 14 Day 21 Day 28 Day 35 Day 56 Day 63 Day 70 Day 77 Day 84 Psespi 1 12.3 14.6 18 23 30.1 34.3 34.1 35.5 35.5 Psespi 2 11.7 11.8 23.4 33.5 42.3 44.1 47.7 47.7 47.5 Psespi 3 10.1 17.8 23 26.5 43.1 43.3 43.2 42.8 47.6 Psespi 4 3.4 10.2 20.9 36.4 39.9 40.1 41.4 45.6 Psespi 5 9.3 29.1 32.2 34.1 41 41.8 Psespi 6 15.3 20.2 28.4 36.4 45.9 45.3 45.3 45.4 47.7 Psespi 7 11.9 19.1 26.1 42.5 42.5 45.4 47.8 49.5 Psespi 8 14.7 20.6 29.6 41.9 41.8 41.8 41.7 41.6 Psespi 9 5.2 10.2 13.9 22.1 31.3 31.1 31.1 31.1 31.1 Psespi 10 9.6 12.5 16.8 27.6 34.5 37 36.8 36.6 36.5 Psespi 11 11.9 17.1 22 32.7 43.6 47.9 47.6 47.7 47.1 Psespi 12 7 13.7 17.1 22 33.6 35.4 35.4 35.7 36.6 Psespi 13 9.1 16.7 23.5 30.2 47.1 46.8 46.5 46.4 46.3 Psespi 14 16.6 17.8 24.7 31.3 38.4 38.8 38.5 38.9 38.7 Psespi 15 7.2 17.2 24.9 32.6 43.5 43.5 43.5 43.4 43.3 Psespi 16 7.1 14 20.8 29.5 38.8 40.8 43.9 46.3 46.1 Psespi 17 7.6 13.5 19.2 26.3 38.8 44.3 44.1 44.1 43.9 Psespi 18 12.3 18.9 14.4 30.9 41.7 41.6 41.6 41.5 41.3 Psespi 19 14 22.1 28.4 36.9 51 51.7 51.6 51.2 51.1 Psespi 20 12.6 20.5 14.1 31.6 41.7 43 38.4 39.4 39.2 Psespi 21 12 16.3 16.2 24.5 37.5 40.6 40.4 39.7 43.4 Psespi 22 10.5 18.7 22.1 35.3 45 48.2 48.2 48.1 48 Psespi 23 8.5 14.5 17.8 24 33 32.9 32.8 32.4 32.6 Psespi 24 9 12.4 15.1 16 38 27.9 38.8 40 40.4 Psespi 25 Psespi 26 11.5 16.2 21.7 28.4 34.9 37.2 36.8 37 37 Psespi 27 11.5 17.3 22.1 27 36.2 36.1 36.1 38.5 39.1 Psespi 28 8.7 15.9 20.1 32.9 45.4 48.5 48.6 48.4 48.3 Psespi 29 14 20.6 22.4 30.9 39.1 39.1 43.1 48.9 48.4 Psespi 30 7 16 20.5 29.4 43 43 42.9 43.3 47.6 Psespi 31 14 17.5 16.7 18.9 26.4 27.4 27.4 27.3 27.5 Psespi 32 6 14 16.6 22 40.8 40.1 40.4 40.2 40.1 Psespi 33 11 16.1 22.9 30.3 48.4 49.1 49.3 49.4 49.1 Psespi 34 13.8 20.1 24 28.6 40 39.9 39.8 39.8 39.7 Psespi 35 5 12.7 22 24.6 23.7 27.1 28.5 Psespi 36 4.2 12 22.7 24.8 27.2 28.3 30.5 Psespi 37 1.7 12.8 17.5 17.3 18.1 20.4 Psespi 38 11.2 14.6 20.4 25.2 39.7 40.9 40.9 40.7 40.6 Psespi 39 11.9 17.7 21.9 28.4 45.4 45 45.1 44.9 44.9 Psespi 40 12 19.8 24.7 30.5 44.2 43.9 44.4 44.1 44